US9277002B2 - Physical resource management - Google Patents

Physical resource management Download PDF

Info

Publication number
US9277002B2
US9277002B2 US14/150,965 US201414150965A US9277002B2 US 9277002 B2 US9277002 B2 US 9277002B2 US 201414150965 A US201414150965 A US 201414150965A US 9277002 B2 US9277002 B2 US 9277002B2
Authority
US
United States
Prior art keywords
physical
server
additional
physical server
pool
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related, expires
Application number
US14/150,965
Other versions
US20150195173A1 (en
Inventor
Manish Gupta
Kim HongJin
Stefan Pappe
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Kyndryl Inc
Original Assignee
International Business Machines Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by International Business Machines Corp filed Critical International Business Machines Corp
Priority to US14/150,965 priority Critical patent/US9277002B2/en
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION reassignment INTERNATIONAL BUSINESS MACHINES CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GUPTA, MANISH, HONGJIN, KIM, PAPPE, STEFAN
Publication of US20150195173A1 publication Critical patent/US20150195173A1/en
Priority to US14/990,258 priority patent/US9584389B2/en
Application granted granted Critical
Publication of US9277002B2 publication Critical patent/US9277002B2/en
Assigned to KYNDRYL, INC. reassignment KYNDRYL, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: INTERNATIONAL BUSINESS MACHINES CORPORATION
Expired - Fee Related legal-status Critical Current
Adjusted expiration legal-status Critical

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/08Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876Network utilisation, e.g. volume of load or congestion level
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network arrangements or protocols for supporting network services or applications
    • H04L67/01Protocols
    • H04L67/10Protocols in which an application is distributed across nodes in the network
    • H04L67/1001Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1004Server selection for load balancing
    • H04L67/1012Server selection for load balancing based on compliance of requirements or conditions with available server resources
    • H04L67/1002
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing data switching networks
    • H04L43/16Threshold monitoring
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00Traffic control in data switching networks
    • H04L47/70Admission control; Resource allocation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network arrangements or protocols for supporting network services or applications
    • H04L67/01Protocols
    • H04L67/10Protocols in which an application is distributed across nodes in the network
    • H04L67/1001Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers

Definitions

  • the present invention relates generally to a method for managing physical resources, and in particular to a method and associated system for generating a free server pool for enabling a physical resource management process.
  • Performing system management includes an inaccurate process with little flexibility. Maintaining elements of a system includes a complicated process that may be time consuming and require a large amount of resources. Accordingly, there exists a need in the art to overcome at least some of the deficiencies and limitations described herein above.
  • a first aspect of the invention provides a method comprising: generating, by a computer processor of a computing system, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by the computer processor, monitored data retrieved during the monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers to the free server pool; determining, by the computer processor, that the physical server pool requires an additional server; rating, by the computer processor, servers within the free server pool based on a calculated chance for required usage within
  • a second aspect of the invention provides a computing system comprising a computer processor coupled to a computer-readable memory unit, the memory unit comprising instructions that when executed by the computer processor implements a method comprising: generating, by the computer processor, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by the computer processor, monitored data retrieved during the monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers to the free server pool; determining, by the computer processor, that the physical server pool
  • a third aspect of the invention provides a computer program product, comprising a computer readable hardware storage device storing a computer readable program code, the computer readable program code comprising an algorithm that when executed by a computer processor of a computer system implements a method, the method comprising: generating, by the computer processor, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by said computer processor, monitored data retrieved during said monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers
  • the present invention advantageously provides a simple method and associated system capable of performing system management.
  • FIG. 1 illustrates a system for sharing physical servers across multiple customers, in accordance with embodiments of the present invention.
  • FIG. 2A illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
  • FIG. 2B illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for allocating servers, in accordance with embodiments of the present invention.
  • FIG. 3 illustrates a computer apparatus used by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
  • FIG. 1 illustrates a system 100 for sharing physical servers across multiple customers, in accordance with embodiments of the present invention.
  • System 100 enables a method for managing physical servers and generating a free server pool 114 for enabling a physical resource management process.
  • System 100 of FIG. 1 includes Physical server pools 108 a . . . 108 m , a free server pool 114 , a virtual machine control module 110 (i.e., comprising any type virtualization manager including, inter alia, vCenter from VMWare, etc.), and a maintenance system 104 .
  • Maintenance system 104 may comprise a hardware/software system.
  • Maintenance system 104 comprises a dense packing finder module 104 a , an optimization detector 104 b , a monitoring module 104 c , a transformation planner module 104 d , a transformation executer module 104 e , and a server cleansing module 104 f .
  • Free server pool (FSP) 114 comprises physical servers (allocated from server pools 108 a . . . 108 m ) that are no longer in use by a customer. Additionally, FSP 114 allows a customer requiring a server to retrieving a server for use.
  • Monitoring system 104 c monitors server pools 108 a . . . 108 m (each belonging to only one customer) for metrics.
  • Monitored metrics may include, inter alia, CPU utilization of virtual machine (VM) processes, physical memory utilization of VM processes, VM to VM network flow processes, etc.
  • Optimization need detector module consumes monitored data (i.e., from monitoring system 104 c ) to determine if a resource utilization rate of any of server pools 108 a . . . 108 m has fallen. If a utilization rate falls below a specified threshold, then decision is executed with respect to freeing a server from use and adding the server to FSP 114 .
  • Dense packing finder module is executed to perform a consolidation process for determining free servers for FSP 114 .
  • the consolidation process provides a target configuration for determining a virtual (VM) associated with a host.
  • Transformation planner component 104 d comprises a component responsible for computing a “low” cost approach to transferring from a current configuration of VMs to a new configuration thereby freeing up specified physical servers.
  • the executed plan comprises migrating VMs from originating hosts to alternative hosts to achieve the transformation.
  • (customer) server pools 108 a . . . 108 m may become highly utilized and demand more physical servers, therefore system 100 allocates a physical server to a customer by retrieving an available server from FSP 114 .
  • System 100 selects a best server from FSP 114 to be presented to a request based on a lower chance of thrashing. Additionally, system 100 achieves a desired configuration with a lower cost of the configuration.
  • System 100 performs the following processes:
  • Scrubbing hosts and a hypervisor before allocating to a new server pool For example, performing an automatic vLAN removal and extension based on a customer selected for a server.
  • a lazy approach to perform a scrubbing process with respect to free servers until needed by a server pool For example, rating free servers based on: a prediction of use within an original server pool, a number of free servers within a same server pool, a variability of load specified for a workload during a recent past time period, etc. in order to help minimize thrashing.
  • Accounting for resources such as, inter alia, memory and network communication between any two VMs, in order to locate out a method for densely packing VMs on hosts. A dense packing process is crucial to maintain a latency of responses by leveraging TCP/IP within a memory structure.
  • System 100 allow physical servers to include a different number of CPUs.
  • Notations associated with processes performed by maintenance system 104 are defined as follows:
  • n number of VMs in a given server pool.
  • m number of physical servers in a given server pool.
  • #c j number of cpus on a given physical server j.
  • cu i and mu i comprise (respectively) a physical CPU and memory utilization (or demands) of the i th VM process.
  • f pq comprises a network flow (bits/sec) between VM p and VM q of a customer. Note that:
  • B. f ii a network flow with components other than VMs such as, inter alia, any components outside of a customer premise within a cloud.
  • the following description comprises a process associated with flows on links due to placement of VMs on servers. If a VM p and a VM q communicate with each other and are placed on a server r and a server s respectively then all communication links connecting physical servers r and s will carry communication traffic between the two VMs. Therefore, an assumption is made with respect to providing a single primary path between any two servers. For example, if servers r and s are connected to a switch, then a path comprises switching and cable connections from the two servers r and s to the switches. If communication is within a server, then the link l corresponds to a software switch in a hypervisor.
  • a link l may include a switch, a router, an actual physical link between a server and a switch, a physical link between two switches, a switch or a router, two routers, etc. Therefore, it is necessary to provide constraints for each of the communication links on the path between any two physical servers as follows:
  • Link(l, r, s) be 1 if the 1 th link is used for communication between r and s, o.w. 0.
  • a total flow on link l due to the placement of all the VMs on servers comprises: ⁇ s ⁇ r>s ⁇ p ⁇ q ⁇ p Link(l, r, s)f pq y pqrs .
  • Optimization detector 104 b enables a process for determining when to free a physical server. The process is described as follows:
  • optimization detector 104 b determines a sum of CPU, memory, and link utilizations.
  • the sum for CPU, memory, link utilizations, and NIC flows are defined respectively as follows: ⁇ j ⁇ i cu i x ij , ⁇ j ⁇ i mu i x ij , and ⁇ s ⁇ r>s ⁇ p ⁇ q ⁇ p Link(l, r, s)f pq y pqrs .
  • the first two terms define CPU and memory, respectively. If any of the following inequalities are true then a process for running an optimization process to densely pack VMs on existing hosts to free one or more hosts is executed: 1.
  • Dense packing finder module 104 a executes a consolidation method, identifies free servers in customer server pools, and computes a rating for safely using a free server for another customer. Additionally, dense packing finder module 104 a determines that once upper thresholds for resource usage by a workload are violated within a measurement interval (i.e., a set of priorities), system 100 raises a demand for adding a free server to support a work load if a server pool comprises a free server. System 100 obtains a new server from FSP 114 for a given customer request for a new physical server as follows:
  • System 100 enables a process for densely packing VMs for freeing servers. Therefore an optimization problem is solved.
  • the objective function of the optimization problem represents a cost that penalizes a configuration comprising usage of excessive servers and therefore to capture this we define z j to be 1 if at least one VM is hosted on physical server j, otherwise z j is defined to be 0.
  • a cost function is defined as ⁇ j #c j z j , where #c j is multiplied such that selecting a server with higher number of CPUs is penalized with respect to selecting another server with lower number of CPUs.
  • z j is expressed in terms of decision variables x ij as follows: ⁇ i x ij ⁇ z j ⁇ x ij , for all i and j.
  • a CPU utilization value is constrained as follows: A sum of the CPU utilizations of the VMs on host j should be upper bounded by CU j and therefore, ⁇ i cu i x ij ⁇ CU j ⁇ #c j *100%.
  • a memory utilization value is constrained as follows: A sum of the memory utilizations of the VMs on host j should be upper bounded by MU j and therefore, ⁇ i mu i x ij ⁇ MU j .
  • a link utilization value is constrained as follows:
  • a total link l utilization of the VMs on host j should be upper bounded by NU lj T l and therefore ⁇ s ⁇ r>s ⁇ p ⁇ q ⁇ p Link(l, r, s)f pq y pqrs ⁇ NU lj T l where NU lj comprises a percentage.
  • Integrity constraints are defined as follows:
  • ⁇ j x ij 1: Each VM i must be hosted on at least one physical server.
  • ⁇ j ⁇ i ⁇ ij n: There are n VMs hosted on at most m physical servers.
  • Co-location constraints are calculated within a workload.
  • ⁇ j #c j z j is minimized and subjected to the following threshold constraints, integrity constraints, and z j x, y constraints:
  • An existing configuration i.e., a current placement of VMs on a host
  • a cost of the transformation depends on a business criticality (e.g., C i , of a VM, where VM i to be migrated is represented in terms of a loss to business if the VM goes down).
  • An overall probability of failure if the VM is migrated e.g., say R i
  • the cost of the transformation depends on a size of the memory state of the VM (i.e., the bigger the memory, the more time it will take for migration and a potentially higher probability of failure due to the software related transient errors).
  • a memory state comprises a memory size of the VM.
  • a normalized memory size is denoted as Mem i .
  • the cost of the transformation is proportional to a rate of change of memory for a VM which is directly proportional to the write-rate of the VM.
  • a process for normalized this number comprises dividing by the sum of the write-rates of all VMs.
  • Cost i max(aC i *R i , bMem i , cWR i )+aC i *R i *bMem i +aC i *R i *cWR i +cWR i *bMem i +aC i *R i *bMem i *cWR i , where a, b, and c are user-defined in [0, 1] interval.
  • the constants a, b, and c are user-defined constants to give relative importance to their associated terms contribution to the overall cost.
  • the aforementioned transformation process results in one or more physical servers bring freed up such that the physical servers are removed from server pool (e.g., server pools 108 a . . . 108 m ) and added to a free server pool (e.g., free server pool 114 ).
  • server pool e.g., server pools 108 a . . . 108 m
  • free server pool e.g., free server pool 114
  • a service provider may stop charging a tenant for that server.
  • key cleansing operations are performed when a physical server is selected for a customer from a free server pool belonging to another customer:
  • the following factors 1 and 2 are associated with a heuristic for estimating a likelihood of choosing a free server from the free server pool when a customer makes a demand for a free server:
  • Factor 1 describes a number of free servers in an original server pool. If a number of free servers comprises a high value then it is determined that a likelihood of a server from the pool being demanded back in its original pool comprises a smaller value. Factor 1 is determined as follows:
  • LFS j is nothing but the fraction:number of free servers in the pool of free server j/total number of free servers.
  • LFS j defines a likelihood that a selected server is not re-requested in the next interval and increases as a number of free servers in the original physical server pool from which it was freed increases.
  • T is a measurement interval for SLO.
  • a demand estimation depends on a combination of history and domain knowledge. For example a combination: a recent history used to predict the demand (i.e., if in the recent history the demand from a customer is low it is expected that to happen in the next interval T), a time of day from past history (i.e., seasonality) to predict the demand, and domain knowledge of expected demand in the interval T.
  • a recent history used to predict the demand i.e., if in the recent history the demand from a customer is low it is expected that to happen in the next interval T
  • a time of day from past history i.e., seasonality
  • LD j comprises one minus a ratio of the demand for server pool k′ to which the server j belongs and the total demand across all the server pools.
  • the overall likelihood for obtaining a free server comprises at least a minimum of the two likelihood components LFS j and LD j .
  • a finer level gradation amongst the servers is further achieved by the product of the two likelihood components LFS j and LD j .
  • a goodness rating of a free server is motivated by the fact that if a free server is included in a server pool and workload components are associated with on the free server it might lead to increased traffic on the vLAN.
  • the following heuristic is used to compute a goodness rating:
  • An overall rating comprises a weighted average of the overall likelihood where weight comprises a goodness rating.
  • FIG. 2A illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
  • Each of the steps in the algorithm of FIG. 2A may be enabled and executed in any order by a computer processor executing computer code.
  • a physical server pool e.g., one of physical server pool 108 a . . . 108 m
  • the physical server pool defines a dedicated group of physical servers associated with a user.
  • step 202 resources of the physical server pool (i.e., generated in step 200 ) and additional resources of additional physical server pools (i.e., defining additional groups of physical servers associated with additional users) are monitored. Each physical server pool of the additional physical server pools is associated with a different user of the additional users.
  • step 204 the monitored utilization resource data retrieved during step 202 is consumed.
  • step 208 the system periodically evaluates a need for consolidating virtual machines in a physical server pool. For example, it may be determined (based on the utilization resource monitoring data) that a utilization rate of the additional physical server pools is less than a specified threshold value.
  • step 209 it is determined (based on results of step 208 ) if a consolidation process should be performed.
  • step 209 it is determined that a consolidation process should not be performed then step 204 is repeated. If in step 209 , it is determined that a consolidation process should be performed then in step 210 , a consolidation process is performed and a new configuration is generated (e.g., a group of physical servers of the additional physical server pools is selected for providing to a logical free server pool). In step 211 , a plan to migrate to a new configuration is determined. In step 212 , the group of physical servers is migrated to the free server pool (i.e., the new configuration) and step 204 is repeated.
  • a new configuration e.g., a group of physical servers of the additional physical server pools is selected for providing to a logical free server pool.
  • a plan to migrate to a new configuration is determined.
  • step 212 the group of physical servers is migrated to the free server pool (i.e., the new configuration) and step 204 is repeated.
  • FIG. 2B illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for allocating servers, in accordance with embodiments of the present invention.
  • Each of the steps in the algorithm of FIG. 2B may be enabled and executed in any order by a computer processor executing computer code.
  • step 220 a need for additional capacity for a physical server pool is detected.
  • step 224 it is determined if a server is available in a free server pool. If in step 224 , it is determined that a server is not available in a free server pool then step 220 is repeated.
  • step 224 it is determined that a server is available in a free server pool then in in step 228 , each physical server pool in the free server pool is rated based on a calculated chance for required usage within an associated physical server pool.
  • step 232 it is determined if a server cleanup process is required. If in step 232 , it is determined that a server cleanup process is required then in step 234 , a cleanup and configuration process is executed with respect to the associated physical server pool and in step 238 , a first physical server of the additional physical server pools is allocated to the physical server pool. If in step 232 , it is determined that a server cleanup process is not required then in step 238 , a first physical server of the additional physical server pools is allocated to the physical server pool.
  • FIG. 3 illustrates a computer apparatus 90 used by system 100 of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
  • the computer system 90 includes a processor 91 , an input device 92 coupled to the processor 91 , an output device 93 coupled to the processor 91 , and memory devices 94 and 95 each coupled to the processor 91 .
  • the input device 92 may be, inter alia, a keyboard, a mouse, a camera, a touchscreen, etc.
  • the output device 93 may be, inter alia, a printer, a plotter, a computer screen, a magnetic tape, a removable hard disk, a floppy disk, etc.
  • the memory devices 94 and 95 may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc.
  • the memory device 95 includes a computer code 97 .
  • the computer code 97 includes algorithms (e.g., the algorithm of FIG. 2 ) for generating a free server pool for enabling a physical resource management process.
  • the processor 91 executes the computer code 97 .
  • the memory device 94 includes input data 96 .
  • the input data 96 includes input required by the computer code 97 .
  • the output device 93 displays output from the computer code 97 .
  • Either or both memory devices 94 and 95 may include the algorithm of FIG. 2 and may be used as a computer usable medium (or a computer readable medium or a program storage device) having a computer readable program code embodied therein and/or having other data stored therein, wherein the computer readable program code includes the computer code 97 .
  • a computer program product (or, alternatively, an article of manufacture) of the computer system 90 may include the computer usable medium (or the program storage device).
  • any of the components of the present invention could be created, integrated, hosted, maintained, deployed, managed, serviced, etc. by a service supplier who offers to generate a free server pool for enabling a physical resource management process.
  • the present invention discloses a process for deploying, creating, integrating, hosting, maintaining, and/or integrating computing infrastructure, including integrating computer-readable code into the computer system 90 , wherein the code in combination with the computer system 90 is capable of performing a method for generating a free server pool for enabling a physical resource management process.
  • the invention provides a business method that performs the process steps of the invention on a subscription, advertising, and/or fee basis.
  • a service supplier such as a Solution Integrator
  • the service supplier can create, maintain, support, etc. a computer infrastructure that performs the process steps of the invention for one or more customers.
  • the service supplier can receive payment from the customer(s) under a subscription and/or fee agreement and/or the service supplier can receive payment from the sale of advertising content to one or more third parties.
  • FIG. 3 shows the computer system 90 as a particular configuration of hardware and software
  • any configuration of hardware and software may be utilized for the purposes stated supra in conjunction with the particular computer system 90 of FIG. 3 .
  • the memory devices 94 and 95 may be portions of a single memory device rather than separate memory devices.

Abstract

A method and system for resource management is provided. The method includes generating a physical server pool. Resources of the physical server pool and additional resources of additional physical server are monitored and monitored data is retrieved during the monitoring. A utilization rate of the additional physical server pools is determined to be less than a threshold value. In response a group of physical servers is migrated to a free server pool. The physical server pool is determined to need an additional server and each physical server pool is rated based on a calculated chance for required usage. A first physical server is allocated to the physical server pool.

Description

FIELD
The present invention relates generally to a method for managing physical resources, and in particular to a method and associated system for generating a free server pool for enabling a physical resource management process.
BACKGROUND
Performing system management includes an inaccurate process with little flexibility. Maintaining elements of a system includes a complicated process that may be time consuming and require a large amount of resources. Accordingly, there exists a need in the art to overcome at least some of the deficiencies and limitations described herein above.
SUMMARY
A first aspect of the invention provides a method comprising: generating, by a computer processor of a computing system, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by the computer processor, monitored data retrieved during the monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers to the free server pool; determining, by the computer processor, that the physical server pool requires an additional server; rating, by the computer processor, servers within the free server pool based on a calculated chance for required usage within an associated physical server pool of the additional physical server pools; and allocating, by the computer processor based on results of the rating, a first physical server of the free server pool to the physical server pool requesting a physical server.
A second aspect of the invention provides a computing system comprising a computer processor coupled to a computer-readable memory unit, the memory unit comprising instructions that when executed by the computer processor implements a method comprising: generating, by the computer processor, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by the computer processor, monitored data retrieved during the monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers to the free server pool; determining, by the computer processor, that the physical server pool requires an additional server; rating, by the computer processor, servers within the free server pool based on a calculated chance for required usage within an associated physical server pool of the additional physical server pools; and allocating, by the computer processor based on results of the rating, a first physical server of the free server pool to the physical server pool requesting a physical server.
A third aspect of the invention provides a computer program product, comprising a computer readable hardware storage device storing a computer readable program code, the computer readable program code comprising an algorithm that when executed by a computer processor of a computer system implements a method, the method comprising: generating, by the computer processor, a physical server pool defining a dedicated group of physical servers associated with a user; monitoring, by the computer processor, resources of the physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of the additional physical server pools is associated with a different user of the additional users; consuming, by said computer processor, monitored data retrieved during said monitoring; first determining, by the computer processor based on the monitoring data, that a utilization rate of the additional physical server pools is less than a specified threshold value; selecting, by the computer processor based on the first determining, a group of physical servers of the additional physical server pools for providing to a logical free server pool; migrating, by the computer processor, the group of physical servers to the free server pool; determining, by the computer processor, that the physical server pool requires an additional server; rating, by the computer processor, servers within the free server pool based on a calculated chance for required usage within an associated physical server pool of the additional physical server pools; and allocating, by the computer processor based on results of the rating, a first physical server of the free server pool to the physical server pool requesting a physical server.
The present invention advantageously provides a simple method and associated system capable of performing system management.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a system for sharing physical servers across multiple customers, in accordance with embodiments of the present invention.
FIG. 2A illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
FIG. 2B illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for allocating servers, in accordance with embodiments of the present invention.
FIG. 3 illustrates a computer apparatus used by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention.
DETAILED DESCRIPTION
FIG. 1 illustrates a system 100 for sharing physical servers across multiple customers, in accordance with embodiments of the present invention. System 100 enables a method for managing physical servers and generating a free server pool 114 for enabling a physical resource management process. System 100 of FIG. 1 includes Physical server pools 108 a . . . 108 m, a free server pool 114, a virtual machine control module 110 (i.e., comprising any type virtualization manager including, inter alia, vCenter from VMWare, etc.), and a maintenance system 104. Maintenance system 104 may comprise a hardware/software system. Maintenance system 104 comprises a dense packing finder module 104 a, an optimization detector 104 b, a monitoring module 104 c, a transformation planner module 104 d, a transformation executer module 104 e, and a server cleansing module 104 f. Free server pool (FSP) 114 comprises physical servers (allocated from server pools 108 a . . . 108 m) that are no longer in use by a customer. Additionally, FSP 114 allows a customer requiring a server to retrieving a server for use. Monitoring system 104 c monitors server pools 108 a . . . 108 m (each belonging to only one customer) for metrics. Monitored metrics may include, inter alia, CPU utilization of virtual machine (VM) processes, physical memory utilization of VM processes, VM to VM network flow processes, etc. Optimization need detector module consumes monitored data (i.e., from monitoring system 104 c) to determine if a resource utilization rate of any of server pools 108 a . . . 108 m has fallen. If a utilization rate falls below a specified threshold, then decision is executed with respect to freeing a server from use and adding the server to FSP 114. Dense packing finder module is executed to perform a consolidation process for determining free servers for FSP 114. The consolidation process provides a target configuration for determining a virtual (VM) associated with a host. Transformation planner component 104 d comprises a component responsible for computing a “low” cost approach to transferring from a current configuration of VMs to a new configuration thereby freeing up specified physical servers. When a plan to achieve a target configuration is obtained, then the plan is executed by transformation executor 104 e. The executed plan comprises migrating VMs from originating hosts to alternative hosts to achieve the transformation. At various times, (customer) server pools 108 a . . . 108 m may become highly utilized and demand more physical servers, therefore system 100 allocates a physical server to a customer by retrieving an available server from FSP 114. System 100 selects a best server from FSP 114 to be presented to a request based on a lower chance of thrashing. Additionally, system 100 achieves a desired configuration with a lower cost of the configuration.
System 100 performs the following processes:
1. Physical server management within a virtualized environment that includes shared storage (on SAN) and LAN.
2. Scrubbing hosts and a hypervisor before allocating to a new server pool. For example, performing an automatic vLAN removal and extension based on a customer selected for a server.
3. A lazy approach to perform a scrubbing process with respect to free servers until needed by a server pool. For example, rating free servers based on: a prediction of use within an original server pool, a number of free servers within a same server pool, a variability of load specified for a workload during a recent past time period, etc. in order to help minimize thrashing.
4. Accounting for resources such as, inter alia, memory and network communication between any two VMs, in order to locate out a method for densely packing VMs on hosts. A dense packing process is crucial to maintain a latency of responses by leveraging TCP/IP within a memory structure.
5. Modeling a cost of migration and providing a method to perform the reconfiguration using a low cost approach. The migration process may include generating a rating/score for an approach dependent on a size of RAM and rate of change of RAM.
6. System 100 allow physical servers to include a different number of CPUs.
Notations associated with processes performed by maintenance system 104 are defined as follows:
1. n=number of VMs in a given server pool.
2. m=number of physical servers in a given server pool.
3. #cj=number of cpus on a given physical server j.
4. cui and mui comprise (respectively) a physical CPU and memory utilization (or demands) of the ith VM process.
5. fpq comprises a network flow (bits/sec) between VM p and VM q of a customer. Note that:
A. fpq=fqp, for each (p, q).
B. fii=a network flow with components other than VMs such as, inter alia, any components outside of a customer premise within a cloud.
6. xij=1 if an ith VM is on the jth host otherwise it is 0.
The following description comprises a process associated with flows on links due to placement of VMs on servers. If a VM p and a VM q communicate with each other and are placed on a server r and a server s respectively then all communication links connecting physical servers r and s will carry communication traffic between the two VMs. Therefore, an assumption is made with respect to providing a single primary path between any two servers. For example, if servers r and s are connected to a switch, then a path comprises switching and cable connections from the two servers r and s to the switches. If communication is within a server, then the link l corresponds to a software switch in a hypervisor. A link l may include a switch, a router, an actual physical link between a server and a switch, a physical link between two switches, a switch or a router, two routers, etc. Therefore, it is necessary to provide constraints for each of the communication links on the path between any two physical servers as follows:
Let Link(l, r, s) be 1 if the 1th link is used for communication between r and s, o.w. 0. A flow contribution on link l if VM p and VM q are situated on server r and s respectively comprises: Link(l, r, s)fpqypqrs, where (xpr+xqs)/2≧ypqrs≧(xpr xqs)/2−½ and ypqrs in {0, 1}(i.e., ypqrs is 1 if p is hosted on r and q is hosted on s otherwise 0). Therefore, a total flow on link l due to the placement of all the VMs on servers comprises: ΣsΣr>sΣpΣq≧pLink(l, r, s)fpqypqrs.
Optimization detector 104 b enables a process for determining when to free a physical server. The process is described as follows:
1. At regular intervals, optimization detector 104 b determines a sum of CPU, memory, and link utilizations. The sum for CPU, memory, link utilizations, and NIC flows are defined respectively as follows: ΣjΣicuixij, ΣjΣimuixij, and ΣsΣr>sΣpΣq≧pLink(l, r, s)fpqypqrs. The first two terms define CPU and memory, respectively. If any of the following inequalities are true then a process for running an optimization process to densely pack VMs on existing hosts to free one or more hosts is executed:
1. Σj #cj 100%−ΣjΣicuixij≧kc 100%, where kc≧1.
2. m 100%−ΣjΣimuixij≧km 100%, where km≧1.
3. m Tl−ΣsΣr>sΣpΣq≧pLink(l, r, s)fpqypqrs≧kl Tl, where Tl is the total capacity of the link l and kl≧1 is the required number of Tl capacity drops required to initiate optimization to densely pack the VMs. kc, km, and kl comprise predefined constants.
Dense packing finder module 104 a: executes a consolidation method, identifies free servers in customer server pools, and computes a rating for safely using a free server for another customer. Additionally, dense packing finder module 104 a determines that once upper thresholds for resource usage by a workload are violated within a measurement interval (i.e., a set of priorities), system 100 raises a demand for adding a free server to support a work load if a server pool comprises a free server. System 100 obtains a new server from FSP 114 for a given customer request for a new physical server as follows:
Create a sorted list of free servers ordered in a descending order of a rating given to a free server that depends on:
1. A likelihood that a server will not be re-requested in an original server pool in the next measurement interval.
a. A goodness rating of the server with respect to a target server pool.
b. Select a topmost free server in a sorted list.
2. Perform a server deactivation process.
3. Scrub a server if a target server pool is different from a source server pool.
4. Extend a vLAN(s) for customers of the server.
5. Register the server with the target server pool.
6. Zone storage pools to the server.
7. Perform a server activation process.
System 100 enables a process for densely packing VMs for freeing servers. Therefore an optimization problem is solved. The objective function of the optimization problem represents a cost that penalizes a configuration comprising usage of excessive servers and therefore to capture this we define zj to be 1 if at least one VM is hosted on physical server j, otherwise zj is defined to be 0. A cost function is defined as Σj#cjzj, where #cj is multiplied such that selecting a server with higher number of CPUs is penalized with respect to selecting another server with lower number of CPUs. zj is expressed in terms of decision variables xij as follows: Σixij≧zj≧xij, for all i and j. When there is no VM on j, xij=0 for all i and therefore Σixij≧zj drives zj to 0, whereas even if there is even one VM on host j then there will exist some i for which xij=1 and therefore zj≧xij will drive zj to 1.
A process for calculating capacity constraints per host j is described as follows:
For each host j, upper bounds are defined. The upper bounds are not be exceeded by any valid configuration that an optimization search problem detects. A CPU utilization value is constrained as follows: A sum of the CPU utilizations of the VMs on host j should be upper bounded by CUj and therefore, Σicuixij≦CUj≦#cj*100%. A memory utilization value is constrained as follows: A sum of the memory utilizations of the VMs on host j should be upper bounded by MUj and therefore, Σimuixij≦MUj. A link utilization value is constrained as follows:
A total link l utilization of the VMs on host j should be upper bounded by NUlj Tl and therefore ΣsΣr>sΣpΣq≧pLink(l, r, s)fpqypqrs≦NUlj Tl where NUlj comprises a percentage.
Integrity constraints are defined as follows:
1. Σjxij=1: Each VM i must be hosted on at least one physical server.
2. ΣjΣiΣij=n: There are n VMs hosted on at most m physical servers.
3. Σjzj≦m−1: At most m physical servers are selected after dense packing Since consolidation is the objective, r.h.s. of the above inequality equals m−1 as at least one server must be freed.
Co-location constraints are calculated within a workload. Co-location constraints comprise constraints for VMs of a workload which may be placed on particular hosts. If there are VMs for a workload which may not be placed on particular hosts then the respective xij variable is defined as 0. If two VMs (e.g., 1 and 3) may not be co-hosted on host j, then the following constraints are added: Σi=1,3xij=1 (anti-colocation).
An overall scenario for performing a dense pack process is described as follows:
Σj#cjzj is minimized and subjected to the following threshold constraints, integrity constraints, and zj x, y constraints:
Threshold Constraints
1. For all servers: Σicuixij≦CUj
2. For all servers' MEM: Σimuixij≦MUj
3. For all links l: ΣsΣr>sΣpΣq≧pLink(l, r, s)fpqypqrs≦NUlj Tl
Integrity Constraints
1. Σjxij=1
2. ΣjΣixij=n
3. Σjzj≦m−1
z, x, and y Constraints
1. Σixij≦zj≦xij, for all i and j
2. (xpr+xqs)/2≧ypqrs≧(xpr+xqs)/2−½ and ypqrs in {0, 1}
An existing configuration (i.e., a current placement of VMs on a host) is transformed by an optimization dense packing process. A cost of the transformation depends on a business criticality (e.g., Ci, of a VM, where VM i to be migrated is represented in terms of a loss to business if the VM goes down). An overall probability of failure if the VM is migrated (e.g., say Ri) comprises an expected cost of: Ci*Ri. Additionally, the cost of the transformation depends on a size of the memory state of the VM (i.e., the bigger the memory, the more time it will take for migration and a potentially higher probability of failure due to the software related transient errors). A memory state comprises a memory size of the VM. A normalized memory size is denoted as Memi. The cost of the transformation is proportional to a rate of change of memory for a VM which is directly proportional to the write-rate of the VM. Let the write-rate of the VM i be WRi. A process for normalized this number comprises dividing by the sum of the write-rates of all VMs. Therefore, the cost of the transformation is defined as Costi:=max(aCi*Ri, bMemi, cWRi)+aCi*Ri*bMemi+aCi*Ri*cWRi+cWRi*bMemi+aCi*Ri*bMemi*cWRi, where a, b, and c are user-defined in [0, 1] interval. The constants a, b, and c are user-defined constants to give relative importance to their associated terms contribution to the overall cost. The aforementioned transformation process results in one or more physical servers bring freed up such that the physical servers are removed from server pool (e.g., server pools 108 a . . . 108 m) and added to a free server pool (e.g., free server pool 114). When a physical server is freed up, a service provider may stop charging a tenant for that server. The following key cleansing operations are performed when a physical server is selected for a customer from a free server pool belonging to another customer:
1. Decommissioning the server for the previous owner.
2. Unregistering the physical server from the server pool to which it belonged.
3. Removing vLAN extensions made to software switches in the physical servers.
4. Unzone storage pools from this server.
5. Performing a service activation process for the new customer.
The following factors 1 and 2 are associated with a heuristic for estimating a likelihood of choosing a free server from the free server pool when a customer makes a demand for a free server:
Factor 1
Factor 1 describes a number of free servers in an original server pool. If a number of free servers comprises a high value then it is determined that a likelihood of a server from the pool being demanded back in its original pool comprises a smaller value. Factor 1 is determined as follows:
1. Let FSkj=1 if the jth server is in the kth server pool, otherwise 0.
2. Define a likelihood of the jth server to not be re-requested in the next interval within its own server pool as: LFSj:=ΣtFSk′tkΣtFSkt, where k′ comprises a server pool to which the jth server belongs.
Essentially LFSj is nothing but the fraction:number of free servers in the pool of free server j/total number of free servers.
LFSj defines a likelihood that a selected server is not re-requested in the next interval and increases as a number of free servers in the original physical server pool from which it was freed increases.
Factor 2
Factor 2 describes a demand in the next interval T (i.e., T is a measurement interval for SLO). A demand estimation depends on a combination of history and domain knowledge. For example a combination: a recent history used to predict the demand (i.e., if in the recent history the demand from a customer is low it is expected that to happen in the next interval T), a time of day from past history (i.e., seasonality) to predict the demand, and domain knowledge of expected demand in the interval T. Various approaches from literature exist to predict demand and any of these can be used in our invention. Factor 2 is determined as follows: Let LDj comprise a likelihood that the jth server is not re-requested for the next interval within its own server pool to which the jth server belongs and LDj:=1−Dk′tDt. LDj comprises one minus a ratio of the demand for server pool k′ to which the server j belongs and the total demand across all the server pools.
An overall likelihood for obtaining a free server j (Rj) is defined as Rj=min(LFSj, LDj)+LFSj*LDj. The overall likelihood for obtaining a free server comprises at least a minimum of the two likelihood components LFSj and LDj. A finer level gradation amongst the servers is further achieved by the product of the two likelihood components LFSj and LDj.
A goodness rating of a free server is motivated by the fact that if a free server is included in a server pool and workload components are associated with on the free server it might lead to increased traffic on the vLAN. The following heuristic is used to compute a goodness rating:
For each VM p in a target server pool's workload that may potentially be hosted on the chosen free server t:
1. initialize #n=1; goodnesst=0.
2. For each VM q for which fpq>0
A. currentFlow:=ΣlΣrΣsLink(l, r, s)fpqypqrs
B. targetFlow:=ΣlΣsLink(l, t, s)fpqypqts, // note that VM p is placed on the new server t
C. goodnesst:=(#n−1)goodnesst/#n+currentFlow/targetFlow/#n
2. goodness=Normalize across all free servers t
3. Output=goodness
An overall rating comprises a weighted average of the overall likelihood where weight comprises a goodness rating.
FIG. 2A illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention. Each of the steps in the algorithm of FIG. 2A may be enabled and executed in any order by a computer processor executing computer code. In step 200, a physical server pool (e.g., one of physical server pool 108 a . . . 108 m) is generated or added. The physical server pool defines a dedicated group of physical servers associated with a user. In step 202, resources of the physical server pool (i.e., generated in step 200) and additional resources of additional physical server pools (i.e., defining additional groups of physical servers associated with additional users) are monitored. Each physical server pool of the additional physical server pools is associated with a different user of the additional users. In step 204, the monitored utilization resource data retrieved during step 202 is consumed. In step 208, the system periodically evaluates a need for consolidating virtual machines in a physical server pool. For example, it may be determined (based on the utilization resource monitoring data) that a utilization rate of the additional physical server pools is less than a specified threshold value. In step 209, it is determined (based on results of step 208) if a consolidation process should be performed. If in step 209, it is determined that a consolidation process should not be performed then step 204 is repeated. If in step 209, it is determined that a consolidation process should be performed then in step 210, a consolidation process is performed and a new configuration is generated (e.g., a group of physical servers of the additional physical server pools is selected for providing to a logical free server pool). In step 211, a plan to migrate to a new configuration is determined. In step 212, the group of physical servers is migrated to the free server pool (i.e., the new configuration) and step 204 is repeated.
FIG. 2B illustrates an algorithm detailing a process flow enabled by the system of FIG. 1 for allocating servers, in accordance with embodiments of the present invention. Each of the steps in the algorithm of FIG. 2B may be enabled and executed in any order by a computer processor executing computer code. In step 220, a need for additional capacity for a physical server pool is detected. In step 224, it is determined if a server is available in a free server pool. If in step 224, it is determined that a server is not available in a free server pool then step 220 is repeated. If in step 224, it is determined that a server is available in a free server pool then in in step 228, each physical server pool in the free server pool is rated based on a calculated chance for required usage within an associated physical server pool. In step 232, it is determined if a server cleanup process is required. If in step 232, it is determined that a server cleanup process is required then in step 234, a cleanup and configuration process is executed with respect to the associated physical server pool and in step 238, a first physical server of the additional physical server pools is allocated to the physical server pool. If in step 232, it is determined that a server cleanup process is not required then in step 238, a first physical server of the additional physical server pools is allocated to the physical server pool.
FIG. 3 illustrates a computer apparatus 90 used by system 100 of FIG. 1 for generating a free server pool for enabling a physical resource management process, in accordance with embodiments of the present invention. The computer system 90 includes a processor 91, an input device 92 coupled to the processor 91, an output device 93 coupled to the processor 91, and memory devices 94 and 95 each coupled to the processor 91. The input device 92 may be, inter alia, a keyboard, a mouse, a camera, a touchscreen, etc. The output device 93 may be, inter alia, a printer, a plotter, a computer screen, a magnetic tape, a removable hard disk, a floppy disk, etc. The memory devices 94 and 95 may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc. The memory device 95 includes a computer code 97. The computer code 97 includes algorithms (e.g., the algorithm of FIG. 2) for generating a free server pool for enabling a physical resource management process. The processor 91 executes the computer code 97. The memory device 94 includes input data 96. The input data 96 includes input required by the computer code 97. The output device 93 displays output from the computer code 97. Either or both memory devices 94 and 95 (or one or more additional memory devices not shown in FIG. 3) may include the algorithm of FIG. 2 and may be used as a computer usable medium (or a computer readable medium or a program storage device) having a computer readable program code embodied therein and/or having other data stored therein, wherein the computer readable program code includes the computer code 97. Generally, a computer program product (or, alternatively, an article of manufacture) of the computer system 90 may include the computer usable medium (or the program storage device).
Still yet, any of the components of the present invention could be created, integrated, hosted, maintained, deployed, managed, serviced, etc. by a service supplier who offers to generate a free server pool for enabling a physical resource management process. Thus the present invention discloses a process for deploying, creating, integrating, hosting, maintaining, and/or integrating computing infrastructure, including integrating computer-readable code into the computer system 90, wherein the code in combination with the computer system 90 is capable of performing a method for generating a free server pool for enabling a physical resource management process. In another embodiment, the invention provides a business method that performs the process steps of the invention on a subscription, advertising, and/or fee basis. That is, a service supplier, such as a Solution Integrator, could offer to generate a free server pool for enabling a physical resource management process. In this case, the service supplier can create, maintain, support, etc. a computer infrastructure that performs the process steps of the invention for one or more customers. In return, the service supplier can receive payment from the customer(s) under a subscription and/or fee agreement and/or the service supplier can receive payment from the sale of advertising content to one or more third parties.
While FIG. 3 shows the computer system 90 as a particular configuration of hardware and software, any configuration of hardware and software, as would be known to a person of ordinary skill in the art, may be utilized for the purposes stated supra in conjunction with the particular computer system 90 of FIG. 3. For example, the memory devices 94 and 95 may be portions of a single memory device rather than separate memory devices.
While embodiments of the present invention have been described herein for purposes of illustration, many modifications and changes will become apparent to those skilled in the art. Accordingly, the appended claims are intended to encompass all such modifications and changes as fall within the true spirit and scope of this invention.

Claims (13)

What is claimed is:
1. A method comprising:
generating, by a computer processor of a computing system, a physical server pool defining a dedicated group of physical servers associated with a user;
monitoring, by said computer processor, resources of said physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of said additional physical server pools is associated with a different user of said additional users;
consuming, by said computer processor, monitored data retrieved during said monitoring;
first determining, by said computer processor based on said monitoring data, that a utilization rate of said additional physical server pools is less than a specified threshold value;
selecting, by said computer processor based on said first determining, a group of physical servers of said additional physical server pools for providing to a logical free server pool, wherein said selecting said group of physical servers of said additional physical server pools for providing to said logical free server pool comprises:
generating a sorted list of free servers ordered in a descending order of ratings calculated for said group of physical servers;
migrating, by said computer processor, said group of physical servers to said free server pool;
determining, by said computer processor, that said physical server pool requires an additional server;
rating, by said computer processor, servers within said free server pool based on a calculated chance for required usage within an associated physical server pool of said additional physical server pools, wherein calculating each of said ratings comprises:
selecting choose a topmost free server of said sorted list;
deactivating said topmost free server;
scrubbing said topmost free server;
extending a vLAN for customers to said topmost free server;
registering said topmost free server with a target server pool; and
zoning storage pools to said topmost free server;
allocating, by said computer processor based on results of said rating, a first physical server of said free server pool to said physical server pool requesting a physical server;
determining, by said computer processor based on a cost analysis, a target configuration associated with allocating associated physical servers of said physical server pool and said additional physical server pools to associated free server pools.
2. The method of claim 1, wherein said monitoring comprises monitoring metrics associated with said physical server pool and said additional physical server pools, and wherein said metrics comprise CPU utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, physical memory utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, and virtual machine to virtual machine network flows for virtual machines associated with said physical server pool and said additional physical server pools.
3. The method of claim 2, wherein said first determining comprises:
determining a sum of utilization values for said metrics; and
running an optimization process with respect to associated virtual machines.
4. The method of claim 1, further comprising:
computing, by said computer processor, a safety rating associated with using a first free server of said group of physical servers for providing to an additional user.
5. The method of claim 1, further comprising:
providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the computing system, said code being executed by the computer processor to implement: said generating, said monitoring, said consuming, said first determining, said selecting, said migrating, said determining, said rating, and said allocating.
6. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a method comprising:
generating, by said computer processor, a physical server pool defining a dedicated group of physical servers associated with a user;
monitoring, by said computer processor, resources of said physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of said additional physical server pools is associated with a different user of said additional users;
consuming, by said computer processor, monitored data retrieved during said monitoring;
first determining, by said computer processor based on said monitoring data, that a utilization rate of said additional physical server pools is less than a specified threshold value;
selecting, by said computer processor based on said first determining, a group of physical servers of said additional physical server pools for providing to a logical free server pool, wherein said selecting said group of physical servers of said additional physical server pools for providing to said logical free server pool comprises:
generating a sorted list of free servers ordered in a descending order of ratings calculated for said group of physical servers;
migrating, by said computer processor, said group of physical servers to said free server pool;
determining, by said computer processor, that said physical server pool requires an additional server;
rating, by said computer processor, servers within said free server pool based on a calculated chance for required usage within an associated physical server pool of said additional physical server pools, wherein calculating each of said ratings comprises:
selecting choose a topmost free server of said sorted list;
deactivating said topmost free server;
scrubbing said topmost free server;
extending a vLAN for customers to said topmost free server;
registering said topmost free server with a target server pool; and
zoning storage pools to said topmost free server;
allocating, by said computer processor based on results of said rating, a first physical server of said free server pool to said physical server pool requesting a physical server;
determining, by said computer processor based on a cost analysis, a target configuration associated with allocating associated physical servers of said physical server pool and said additional physical server pools to associated free server pools.
7. The computing system of claim 6, wherein said monitoring comprises monitoring metrics associated with said physical server pool and said additional physical server pools, and wherein said metrics comprise CPU utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, physical memory utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, and virtual machine to virtual machine network flows for virtual machines associated with said physical server pool and said additional physical server pools.
8. The computing system of claim 7, wherein said first determining comprises:
determining a sum of utilization values for said metrics; and
running an optimization process with respect to associated virtual machines.
9. The computing system of claim 6, wherein said method further comprises:
computing, by said computer processor, a safety rating associated with using a first free server of said group of physical servers for providing to an additional user.
10. A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a computer processor of a computer system implements a method, said method comprising:
generating, by said computer processor, a physical server pool defining a dedicated group of physical servers associated with a user;
monitoring, by said computer processor, resources of said physical server pool and additional resources of additional physical server pools defining additional groups of physical servers associated with additional users, wherein each physical server pool of said additional physical server pools is associated with a different user of said additional users;
consuming, by said computer processor, monitored data retrieved during said monitoring;
first determining, by said computer processor based on said monitoring data, that a utilization rate of said additional physical server pools is less than a specified threshold value;
selecting, by said computer processor based on said first determining, a group of physical servers of said additional physical server pools for providing to a logical free server pool, wherein said selecting said group of physical servers of said additional physical server pools for providing to said logical free server pool comprises:
generating a sorted list of free servers ordered in a descending order of ratings calculated for said group of physical servers;
migrating, by said computer processor, said group of physical servers to said free server pool;
determining, by said computer processor, that said physical server pool requires an additional server;
rating, by said computer processor, servers within said free server pool based on a calculated chance for required usage within an associated physical server pool of said additional physical server pools, wherein calculating each of said ratings comprises:
selecting choose a topmost free server of said sorted list;
deactivating said topmost free server;
scrubbing said topmost free server;
extending a vLAN for customers to said topmost free server;
registering said topmost free server with a target server pool; and
zoning storage pools to said topmost free server;
allocating, by said computer processor based on results of said rating, a first physical server of said free server pool to said physical server pool requesting a physical server;
determining, by said computer processor based on a cost analysis, a target configuration associated with allocating associated physical servers of said physical server pool and said additional physical server pools to associated free server pools.
11. The computer program product of claim 10, wherein said monitoring comprises monitoring metrics associated with said physical server pool and said additional physical server pools, and wherein said metrics comprise CPU utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, physical memory utilization metrics for virtual machine processes associated with said physical server pool and said additional physical server pools, and virtual machine to virtual machine network flows for virtual machines associated with said physical server pool and said additional physical server pools.
12. The computer program product of claim 11, wherein said first determining comprises:
determining a sum of utilization values for said metrics; and
running an optimization process with respect to associated virtual machines.
13. The computer program product of claim 10, wherein said method further comprises:
computing, by said computer processor, a safety rating associated with using a first free server of said group of physical servers for providing to an additional user.
US14/150,965 2014-01-09 2014-01-09 Physical resource management Expired - Fee Related US9277002B2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US14/150,965 US9277002B2 (en) 2014-01-09 2014-01-09 Physical resource management
US14/990,258 US9584389B2 (en) 2014-01-09 2016-01-07 Physical resource management

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US14/150,965 US9277002B2 (en) 2014-01-09 2014-01-09 Physical resource management

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US14/990,258 Continuation US9584389B2 (en) 2014-01-09 2016-01-07 Physical resource management

Publications (2)

Publication Number Publication Date
US20150195173A1 US20150195173A1 (en) 2015-07-09
US9277002B2 true US9277002B2 (en) 2016-03-01

Family

ID=53496054

Family Applications (2)

Application Number Title Priority Date Filing Date
US14/150,965 Expired - Fee Related US9277002B2 (en) 2014-01-09 2014-01-09 Physical resource management
US14/990,258 Active US9584389B2 (en) 2014-01-09 2016-01-07 Physical resource management

Family Applications After (1)

Application Number Title Priority Date Filing Date
US14/990,258 Active US9584389B2 (en) 2014-01-09 2016-01-07 Physical resource management

Country Status (1)

Country Link
US (2) US9277002B2 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10228961B2 (en) 2016-06-15 2019-03-12 Red Hat Israel, Ltd. Live storage domain decommissioning in a virtual environment

Families Citing this family (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9942083B1 (en) * 2012-09-10 2018-04-10 Amazon Technologies, Inc. Capacity pool management
US9277002B2 (en) 2014-01-09 2016-03-01 International Business Machines Corporation Physical resource management
US9923965B2 (en) 2015-06-05 2018-03-20 International Business Machines Corporation Storage mirroring over wide area network circuits with dynamic on-demand capacity
US10216441B2 (en) 2015-11-25 2019-02-26 International Business Machines Corporation Dynamic quality of service for storage I/O port allocation
US10177993B2 (en) 2015-11-25 2019-01-08 International Business Machines Corporation Event-based data transfer scheduling using elastic network optimization criteria
US10581680B2 (en) 2015-11-25 2020-03-03 International Business Machines Corporation Dynamic configuration of network features
US9923784B2 (en) * 2015-11-25 2018-03-20 International Business Machines Corporation Data transfer using flexible dynamic elastic network service provider relationships
US10057327B2 (en) 2015-11-25 2018-08-21 International Business Machines Corporation Controlled transfer of data over an elastic network
US9923839B2 (en) 2015-11-25 2018-03-20 International Business Machines Corporation Configuring resources to exploit elastic network capability
US10397312B2 (en) * 2016-12-16 2019-08-27 Visa International Service Association Automated server deployment platform
US10999135B2 (en) * 2018-09-19 2021-05-04 Google Llc Fast provisioning in cloud computing environments
US11216295B2 (en) 2019-01-21 2022-01-04 Vmware, Inc. Systems and methods for recommending optimized virtual-machine configurations
US11595319B2 (en) * 2020-12-21 2023-02-28 Microsoft Technology Licensing, Llc Differential overbooking in a cloud computing environment
CN114448897B (en) * 2021-12-29 2024-01-02 天翼云科技有限公司 Target migration method and device

Citations (45)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020156984A1 (en) * 2001-02-20 2002-10-24 Storageapps Inc. System and method for accessing a storage area network as network attached storage
US20030018927A1 (en) * 2001-07-23 2003-01-23 Gadir Omar M.A. High-availability cluster virtual server system
US20030079019A1 (en) * 2001-09-28 2003-04-24 Lolayekar Santosh C. Enforcing quality of service in a storage network
US6598071B1 (en) * 1998-07-27 2003-07-22 Hitachi, Ltd. Communication apparatus and method of hand over of an assigned group address from one communication apparatus to another
US20030177176A1 (en) * 2002-03-18 2003-09-18 Hirschfeld Robert A. Near on-line servers
US20040051731A1 (en) * 2002-09-16 2004-03-18 Chang David Fu-Tien Software application domain and storage domain interface process and method
US20040054780A1 (en) * 2002-09-16 2004-03-18 Hewlett-Packard Company Dynamic adaptive server provisioning for blade architectures
US20050021848A1 (en) * 2000-10-13 2005-01-27 Jorgenson Daniel Scott System and method for distributing load among redundant independent stateful World Wide Web server sites
US20050038890A1 (en) * 2003-08-11 2005-02-17 Hitachi., Ltd. Load distribution method and client-server system
US20050091215A1 (en) 2003-09-29 2005-04-28 Chandra Tushar D. Technique for provisioning storage for servers in an on-demand environment
US20050091217A1 (en) * 2003-10-24 2005-04-28 Schlangen Thomas J. Server selection method
US6976134B1 (en) * 2001-09-28 2005-12-13 Emc Corporation Pooling and provisioning storage resources in a storage network
US20070078988A1 (en) * 2005-09-15 2007-04-05 3Tera, Inc. Apparatus, method and system for rapid delivery of distributed applications
US20070233866A1 (en) * 2006-03-28 2007-10-04 Karen Appleby Method and system for dynamically allocating servers to compute-resources using capacity thresholds
US20070260721A1 (en) * 2006-05-02 2007-11-08 Patrick Glen Bose Physical server discovery and correlation
US20070258388A1 (en) * 2006-05-02 2007-11-08 Patrick Glen Bose Virtual server cloning
US20070297428A1 (en) * 2006-06-26 2007-12-27 Patrick Glen Bose Port pooling
US20080027961A1 (en) * 2006-07-28 2008-01-31 Arlitt Martin F Data assurance in server consolidation
US20080205377A1 (en) * 2007-02-22 2008-08-28 Blade Network Technologies, Inc. System and methods for providing server virtualization assistance
US7478107B1 (en) * 2004-12-23 2009-01-13 Emc Corporation Methods and apparatus facilitating management of a SAN
US20090019535A1 (en) * 2007-07-10 2009-01-15 Ragingwire Enterprise Solutions, Inc. Method and remote system for creating a customized server infrastructure in real time
US7503045B1 (en) * 1999-08-23 2009-03-10 Sun Microsystems, Inc. Extensible computing system
US20090222544A1 (en) * 2008-03-03 2009-09-03 Microsoft Corporation Framework for joint analysis and design of server provisioning and load dispatching for connection-intensive server
US20090222562A1 (en) * 2008-03-03 2009-09-03 Microsoft Corporation Load skewing for power-aware server provisioning
US20100095004A1 (en) * 2008-10-15 2010-04-15 Patentvc Ltd. Balancing a distributed system by replacing overloaded servers
US20100094967A1 (en) * 2008-10-15 2010-04-15 Patentvc Ltd. Large Scale Distributed Content Delivery Network
US7703102B1 (en) * 1999-08-23 2010-04-20 Oracle America, Inc. Approach for allocating resources to an apparatus based on preemptable resource requirements
US20100162032A1 (en) * 2008-12-23 2010-06-24 David Dodgson Storage availability using cryptographic splitting
US8032634B1 (en) * 1999-08-23 2011-10-04 Oracle America, Inc. Approach for allocating resources to an apparatus based on resource requirements
US20120054346A1 (en) * 2010-08-26 2012-03-01 Futurewei Technologies, Inc. Method and System for Cross-Stratum Optimization in Application-Transport Networks
US20120066371A1 (en) * 2010-09-10 2012-03-15 Cisco Technology, Inc. Server Load Balancer Scaling for Virtual Servers
US8179809B1 (en) * 1999-08-23 2012-05-15 Oracle America, Inc. Approach for allocating resources to an apparatus based on suspendable resource requirements
US20120233418A1 (en) * 2011-03-08 2012-09-13 Rackspace Us, Inc. Massively scalable object storage
US20120233316A1 (en) * 2011-03-08 2012-09-13 Hitachi, Ltd. Management computer, storage system management method, and storage system
US20120254443A1 (en) * 2011-03-30 2012-10-04 International Business Machines Corporation Information processing system, information processing apparatus, method of scaling, program, and recording medium
US20120297068A1 (en) * 2011-05-19 2012-11-22 International Business Machines Corporation Load Balancing Workload Groups
US20120324082A1 (en) * 2011-06-17 2012-12-20 Futurewei Technologies, Inc. Cloud Service Control and Management Architecture Expanded to Interface the Network Stratum
US20130013783A1 (en) 2004-12-22 2013-01-10 International Business Machines Corporation System, method and computer program product for provisioning of resources and service environments
US20130080626A1 (en) * 2011-09-26 2013-03-28 Limelight Networks, Inc. Edge-based resource spin-up for cloud computing
US20130111467A1 (en) * 2011-10-27 2013-05-02 Cisco Technology, Inc. Dynamic Server Farms
US20130173809A1 (en) * 2011-12-30 2013-07-04 Certona Corporation Fault tolerance and maintaining service response under unanticipated load conditions
US8484355B1 (en) * 2008-05-20 2013-07-09 Verizon Patent And Licensing Inc. System and method for customer provisioning in a utility computing platform
US20140047084A1 (en) * 2012-08-07 2014-02-13 Advanced Micro Devices, Inc. System and method for modifying a hardware configuration of a cloud computing system
US20140279201A1 (en) * 2013-03-15 2014-09-18 Gravitant, Inc. Assessment of best fit cloud deployment infrastructures
US20150222516A1 (en) * 2012-12-18 2015-08-06 Jim Daubert Techniques Associated with Server Transaction Latency Information

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7769843B2 (en) * 2006-09-22 2010-08-03 Hy Performix, Inc. Apparatus and method for capacity planning for data center server consolidation and workload reassignment
US9411653B2 (en) * 2008-04-11 2016-08-09 Adobe Systems Incorporated System and method for provisioning and load balancing user accounts on server clusters
US8874749B1 (en) * 2010-02-03 2014-10-28 Citrix Systems, Inc. Network fragmentation and virtual machine migration in a scalable cloud computing environment
US8806015B2 (en) * 2011-05-04 2014-08-12 International Business Machines Corporation Workload-aware placement in private heterogeneous clouds
US9106482B1 (en) * 2012-07-24 2015-08-11 Google Inc. Systems and methods for proxy-less load balancing
EP2701064B1 (en) * 2012-08-24 2019-04-10 Hasso-Plattner-Institut für Softwaresystemtechnik GmbH Robust tenant placement and migration in database-as-a-service environments
US9282166B2 (en) * 2012-11-29 2016-03-08 International Business Machines Corporation Management infrastructure analysis for cloud migration
US9432301B2 (en) * 2013-04-29 2016-08-30 Telefonaktiebolaget L M Ericsson (Publ) Defining disjoint node groups for virtual machines with pre-existing placement policies
US9350800B2 (en) * 2013-06-05 2016-05-24 Microsoft Technology Licensing, Llc Defragmenting clusters with reserved resources
US9363192B2 (en) * 2013-10-31 2016-06-07 Vmware, Inc. Automatic remediation in a distributed computer system with multiple clusters of host computers
US20150178137A1 (en) * 2013-12-23 2015-06-25 Microsoft Corporation Dynamic system availability management
US9277002B2 (en) 2014-01-09 2016-03-01 International Business Machines Corporation Physical resource management
US9424065B2 (en) * 2014-06-26 2016-08-23 Vmware, Inc. Methods and apparatus to scale application deployments in cloud computing environments using virtual machine pools
US9497123B2 (en) * 2014-12-18 2016-11-15 Telefonaktiebolaget L M Ericsson (Publ) Method and system for load balancing in a software-defined networking (SDN) system upon server reconfiguration

Patent Citations (46)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6598071B1 (en) * 1998-07-27 2003-07-22 Hitachi, Ltd. Communication apparatus and method of hand over of an assigned group address from one communication apparatus to another
US7503045B1 (en) * 1999-08-23 2009-03-10 Sun Microsystems, Inc. Extensible computing system
US8179809B1 (en) * 1999-08-23 2012-05-15 Oracle America, Inc. Approach for allocating resources to an apparatus based on suspendable resource requirements
US8032634B1 (en) * 1999-08-23 2011-10-04 Oracle America, Inc. Approach for allocating resources to an apparatus based on resource requirements
US7703102B1 (en) * 1999-08-23 2010-04-20 Oracle America, Inc. Approach for allocating resources to an apparatus based on preemptable resource requirements
US20050021848A1 (en) * 2000-10-13 2005-01-27 Jorgenson Daniel Scott System and method for distributing load among redundant independent stateful World Wide Web server sites
US20020156984A1 (en) * 2001-02-20 2002-10-24 Storageapps Inc. System and method for accessing a storage area network as network attached storage
US20030018927A1 (en) * 2001-07-23 2003-01-23 Gadir Omar M.A. High-availability cluster virtual server system
US6976134B1 (en) * 2001-09-28 2005-12-13 Emc Corporation Pooling and provisioning storage resources in a storage network
US20030079019A1 (en) * 2001-09-28 2003-04-24 Lolayekar Santosh C. Enforcing quality of service in a storage network
US20030177176A1 (en) * 2002-03-18 2003-09-18 Hirschfeld Robert A. Near on-line servers
US7765299B2 (en) 2002-09-16 2010-07-27 Hewlett-Packard Development Company, L.P. Dynamic adaptive server provisioning for blade architectures
US20040054780A1 (en) * 2002-09-16 2004-03-18 Hewlett-Packard Company Dynamic adaptive server provisioning for blade architectures
US20040051731A1 (en) * 2002-09-16 2004-03-18 Chang David Fu-Tien Software application domain and storage domain interface process and method
US20050038890A1 (en) * 2003-08-11 2005-02-17 Hitachi., Ltd. Load distribution method and client-server system
US20050091215A1 (en) 2003-09-29 2005-04-28 Chandra Tushar D. Technique for provisioning storage for servers in an on-demand environment
US20050091217A1 (en) * 2003-10-24 2005-04-28 Schlangen Thomas J. Server selection method
US20130013783A1 (en) 2004-12-22 2013-01-10 International Business Machines Corporation System, method and computer program product for provisioning of resources and service environments
US7478107B1 (en) * 2004-12-23 2009-01-13 Emc Corporation Methods and apparatus facilitating management of a SAN
US20070078988A1 (en) * 2005-09-15 2007-04-05 3Tera, Inc. Apparatus, method and system for rapid delivery of distributed applications
US20070233866A1 (en) * 2006-03-28 2007-10-04 Karen Appleby Method and system for dynamically allocating servers to compute-resources using capacity thresholds
US20070258388A1 (en) * 2006-05-02 2007-11-08 Patrick Glen Bose Virtual server cloning
US20070260721A1 (en) * 2006-05-02 2007-11-08 Patrick Glen Bose Physical server discovery and correlation
US20070297428A1 (en) * 2006-06-26 2007-12-27 Patrick Glen Bose Port pooling
US20080027961A1 (en) * 2006-07-28 2008-01-31 Arlitt Martin F Data assurance in server consolidation
US20080205377A1 (en) * 2007-02-22 2008-08-28 Blade Network Technologies, Inc. System and methods for providing server virtualization assistance
US20090019535A1 (en) * 2007-07-10 2009-01-15 Ragingwire Enterprise Solutions, Inc. Method and remote system for creating a customized server infrastructure in real time
US20090222544A1 (en) * 2008-03-03 2009-09-03 Microsoft Corporation Framework for joint analysis and design of server provisioning and load dispatching for connection-intensive server
US20090222562A1 (en) * 2008-03-03 2009-09-03 Microsoft Corporation Load skewing for power-aware server provisioning
US8484355B1 (en) * 2008-05-20 2013-07-09 Verizon Patent And Licensing Inc. System and method for customer provisioning in a utility computing platform
US20100094967A1 (en) * 2008-10-15 2010-04-15 Patentvc Ltd. Large Scale Distributed Content Delivery Network
US20100095004A1 (en) * 2008-10-15 2010-04-15 Patentvc Ltd. Balancing a distributed system by replacing overloaded servers
US20100162032A1 (en) * 2008-12-23 2010-06-24 David Dodgson Storage availability using cryptographic splitting
US20120054346A1 (en) * 2010-08-26 2012-03-01 Futurewei Technologies, Inc. Method and System for Cross-Stratum Optimization in Application-Transport Networks
US20120066371A1 (en) * 2010-09-10 2012-03-15 Cisco Technology, Inc. Server Load Balancer Scaling for Virtual Servers
US20120233418A1 (en) * 2011-03-08 2012-09-13 Rackspace Us, Inc. Massively scalable object storage
US20120233316A1 (en) * 2011-03-08 2012-09-13 Hitachi, Ltd. Management computer, storage system management method, and storage system
US20120254443A1 (en) * 2011-03-30 2012-10-04 International Business Machines Corporation Information processing system, information processing apparatus, method of scaling, program, and recording medium
US20120297068A1 (en) * 2011-05-19 2012-11-22 International Business Machines Corporation Load Balancing Workload Groups
US20120324082A1 (en) * 2011-06-17 2012-12-20 Futurewei Technologies, Inc. Cloud Service Control and Management Architecture Expanded to Interface the Network Stratum
US20130080626A1 (en) * 2011-09-26 2013-03-28 Limelight Networks, Inc. Edge-based resource spin-up for cloud computing
US20130111467A1 (en) * 2011-10-27 2013-05-02 Cisco Technology, Inc. Dynamic Server Farms
US20130173809A1 (en) * 2011-12-30 2013-07-04 Certona Corporation Fault tolerance and maintaining service response under unanticipated load conditions
US20140047084A1 (en) * 2012-08-07 2014-02-13 Advanced Micro Devices, Inc. System and method for modifying a hardware configuration of a cloud computing system
US20150222516A1 (en) * 2012-12-18 2015-08-06 Jim Daubert Techniques Associated with Server Transaction Latency Information
US20140279201A1 (en) * 2013-03-15 2014-09-18 Gravitant, Inc. Assessment of best fit cloud deployment infrastructures

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Andrzejak et al; Bounding the Resource Savings of Utility Computing Models; Internet Systems and Storage Laboratory, Hewlett Packard Laboratories; HPL-2002-339; Dec. 6, 2002; 22 pages.
Gmach et al.; Selling T-shirts and Time Shares in the Cloud; 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing; May 13-16, 2012; pp. 539-546.

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10228961B2 (en) 2016-06-15 2019-03-12 Red Hat Israel, Ltd. Live storage domain decommissioning in a virtual environment

Also Published As

Publication number Publication date
US9584389B2 (en) 2017-02-28
US20150195173A1 (en) 2015-07-09
US20160119212A1 (en) 2016-04-28

Similar Documents

Publication Publication Date Title
US9584389B2 (en) Physical resource management
US10587682B2 (en) Resource allocation diagnosis on distributed computer systems
US11003492B2 (en) Virtual machine consolidation
EP3525096B1 (en) Resource load balancing control method and cluster scheduler
US20220078036A1 (en) Asset management with respect to a shared pool of configurable computing resources
US10623481B2 (en) Balancing resources in distributed computing environments
LaCurts et al. Cicada: Introducing predictive guarantees for cloud networks
Shen et al. A resource usage intensity aware load balancing method for virtual machine migration in cloud datacenters
US9424063B2 (en) Method and system for generating remediation options within a cluster of host computers that run virtual machines
US20150058844A1 (en) Virtual computing resource orchestration
Householder et al. On cloud-based oversubscription
EP4029197B1 (en) Utilizing network analytics for service provisioning
US11150944B2 (en) Balancing mechanisms in ordered lists of dispatch queues in a computational device
WO2015101419A1 (en) Method and system for allocating resources to resource consumers in a cloud computing environment
CN106133693A (en) The moving method of virtual machine, device and equipment
US20170187790A1 (en) Ranking system
Kaur et al. Proactive scheduling in cloud computing
US10394612B2 (en) Methods and systems to evaluate data center performance and prioritize data center objects and anomalies for remedial actions
Chouliaras et al. Auto-scaling containerized cloud applications: A workload-driven approach
Lee et al. Resource reallocation of virtual machine in cloud computing with MCDM algorithm
Hacker Toward a reliable cloud computing service
Verma et al. Rank based ant colony optimization for energy efficient VM placement on cloud
Thakur et al. Performance Evaluation of Server Consolidation Algorithm in Virtualized Cloud Environment with Constant Load
Bräscher et al. Improving cloud computing virtual machines balancing through hosts and virtual machines similarities
Mahalingam et al. Energy aware resource management in distributed cloud computing with overload avoidance

Legal Events

Date Code Title Description
AS Assignment

Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GUPTA, MANISH;HONGJIN, KIM;PAPPE, STEFAN;SIGNING DATES FROM 20131119 TO 20131120;REEL/FRAME:031926/0407

STCF Information on status: patent grant

Free format text: PATENTED CASE

FEPP Fee payment procedure

Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

LAPS Lapse for failure to pay maintenance fees

Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

STCH Information on status: patent discontinuation

Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362

FP Lapsed due to failure to pay maintenance fee

Effective date: 20200301

AS Assignment

Owner name: KYNDRYL, INC., NEW YORK

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INTERNATIONAL BUSINESS MACHINES CORPORATION;REEL/FRAME:057885/0644

Effective date: 20210930